Abstract

The purpose of this research study was to predict and explain elementary and secondary preservice teachers' continuance behavioral intentions and pedagogical usage of Twitter, a web based social networking, microblogging platform, to build professional growth and capital. The objective of the research study was to examine preservice teachers' beliefs associated with the specified constructs that formed the latent variables of the hypothesized research model; these latent variables were then measured with their associated indicators or manifest variables, and the relationship between the manifest variables was examined through the Structural Equation Modeling (SEM) process. A non-experimental empirical research study was conducted using the survey methodology; purposive, criterion referenced, sampling of elementary and secondary preservice teachers, N=379, was employed using social media platforms and intern listserv at a large Southeastern university. The final sample of N= 250 participants was determined through the process of regression imputation of elementary and secondary preservice teachers' survey responses. The results demonstrated that constructs of the extended Technology Acceptance Model showed significant goodness-of-fit indices and coefficients of determination after analyzing the data from the survey. Implications of this research contribute significantly toward teacher education and training by providing insights into the factors that impact the pedagogical use of Twitter, a web-based social networking and microblogging platform, for building professional capital in preservice teachers.

Notes

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Graduation Date

2016

Semester

Summer

Advisor

Sivo, Stephen

Degree

Doctor of Philosophy (Ph.D.)

College

College of Education and Human Performance

Degree Program

Education; Elementary Education

Format

application/pdf

Identifier

CFE0006314

URL

http://purl.fcla.edu/fcla/etd/CFE0006314

Language

English

Release Date

August 2021

Length of Campus-only Access

5 years

Access Status

Doctoral Dissertation (Open Access)

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